A new paper co-authored by School of Computing faculty and students was recently highlighted in a Hackster.io article.
The paper, “Wet TinyML: Chemical Neural Network Using Gene Regulation and Cell Plasticity,” was co-authored by Associate Professor Sasitharan Balasubramaniam, Dale M. Jensen Chair Mehmet Can Vuran, Director and Professor Witawas Srisa-an, and graduate students Samitha Somathilaka and Adrian Ratwatte. The School of Computing authors also collaborated with Professor Pietro Liò of the University of Cambridge.
The paper explores the team's previously investigated concept of Gene Regulatory Neural Network (GRNN), which utilizes natural neural network-like structures inherent in biological cells, or Wet TinyML, to perform computing tasks using chemical inputs. The new paper builds upon this concept by incorporating cell plasticity, to further exploit natural cell’s adaptability, in order to diversify the GRNN search that can match larger spectrum as well as dynamic computing tasks.
Read the full paper here.